Wie analysieren und priorisieren Sie das Feedback, das Sie aus Ihren MVP-Tests erhalten?

You need to be specific in your questions for your early customers. Don't just say "What do you think" Ask them what features did they use the most and why? What if anything could be improved ? How smooth was the onboarding to the platform or service and how can it be made better? What impact has using this product or service had on your business and why?

One thing I've learned that is helpful for startups working towards an MVP is creating metrics to measure. Where a physical product or software/app, there are metrics you can check against to ensure you're solving the right problems. Some metrics might be number of launches, how often someone spends in your app, how long does it take for a user to get from open to value attained. When it comes to creating an MVP you should know what makes it minimal and this should be a subset of everything that you think adds value. Also understand how to dissect your feedback so you don't add more just because people ask for it but that it truly services the product in the short term for success.

Prioritize based on which types of feedback show up again and again, especially from folks who won't buy your product unless you build the feature they're mentioning. This way, building that feature opens up a new customer segment that wasn't available before. For the product I built (a drag & drop tool to simplify business finance for founders), It wasn't enough for my UI to be great; the feedback I got over and over was that QuickBooks and Xero integrations were requirements, not nice-to-haves. Folks don't want to re-type financial data by hand into a new system, they want an automatic sync. Prioritizing this feedback and building these features definitely changed the conversation with prospects going forward.

- When evaluating feedback, start by grouping responses into categories like usability, feature requests, and bugs. - Look for recurring themes and issues mentioned by multiple users to see what stood out. Then, assess how each piece of feedback would impact user experience and your business goals. - Prioritize what was urgent and important first, balancing quick wins with more significant improvements. Then discuss these priorities with your team to ensure they were all on the same page. - Use tools like Asana to organize and track the implementation of feedback. This method helps efficiently address the most impactful areas for improvement.

After analyzing and categorizing the feedback, maintain an open and ongoing dialogue with your user community. This helps in validating any changes or improvements made based on their feedback. Additionally, consider implementing feedback loops within your product development cycle to ensure continuous alignment with user needs and preferences. This iterative approach not only strengthens your product but also builds trust and loyalty among your user base.

Group your feedback based on recurring themes or topics. This could involve categorising by feature, user experience, bugs, or overall impression. Not all feedback carries equal weight. While all feedback is valuable, consider the user's experience level, technical expertise, and the context of their feedback when evaluating its significance.

Analyzing and prioritizing feedback from MVP testing involves several key steps. Initially, collect quantitative feedback via surveys and analytics, and qualitative insights through interviews and focus groups. Categorize this feedback using affinity maps and feedback matrices. Quantitative analysis might reveal average ratings and user behavior patterns, while qualitative analysis highlights themes and user personas. Synthesizing feedback involves recognizing patterns, trends, and opportunities. Finally, prioritize feedback by clustering similar comments, using matrices to rank by impact and effort, and applying frameworks like MoSCoW. This structured approach ensures your MVP evolves effectively based on user needs and preferences.

This is a great example of how ChatGPT can help! A quick Google search can list many prompts to use, but generally speaking, you copy-paste your questions and responses and then have a computer run the analysis for you. You'll still want to manually review the data yourself, but this approach can help you avoid confirmation bias. An MVP should be testing at least one of your riskiest assumptions and should solve at least one major pain point for the user. Your questions (and your analysis) should be focused on how well you are achieving those goals.

Use a prioritization framework such as PIE, ICE, or RICE, which will help you assess the value, impact, and ease of implementation for each new feature. Start with the ones that have the highest scores and are most crucial to the target group.

In the journey of validating an early-stage startup, understanding which assumptions carry the highest risk is a pivotal step prior to gathering feedback. These high-risk assumptions are the bedrock of your MVP; they hold make-or-break potential as they are deeply embedded in the core of your idea. Addressing these assumptions first and seeking targeted feedback can dramatically streamline the validation process. By doing so, founders can learn whether the core concept of their product resonates with market needs or requires a pivot. Regardless, what the outcome is, the goal is to get to one as quickly as possible.